Data protection is a common component of most computing systems. Data protection software such as backup applications, which protect data by storing backup data sets of source data sets, are under pressure to do more with fewer resources and optimize costs. Over time, data protection software has made many improvements. Backups, for example, can be de-duplicated and the backup data sets are configured such that is possible to restore data as the data existed at various points in time. Backup sets can also be stored in the cloud. When backup data sets or other data is stored in the cloud, IT (Information Technology) as a service often plays a role. A backup application can be provided as a service, although the backup application is still associated with software components.
Some backup applications today use the cloud to store backup data sets. In these situations, however, no consideration is given to the data that is being backed up. The backup data sets are simply moved to the cloud: client x is backed up to target y. This can result in potential problems. For example, current backup applications do not classify the data or consider the type of data being backed up. In systems where data is not classified in the context of where the backup data set will be stored, the backup application does not have the ability to dynamically adjust the target or destination of the backup data set to the type of data included in the backup data set. For example, if characteristics of the source data set change, conventional backup applications do not reconsider where the backup data sets is stored. Rather, the destination or target on which the backup data set is stored may depend on the client name. Further, conventional backup applications do not have the ability to scale.
Systems and methods are needed to intelligently disseminate data sets including backup data sets to targets. Systems and methods are need that can dynamically adjust the destination or target based when the source data changes.